il13pred

Introduction

IL13Pred is developed for predicting, desiging, and scanning the interleukin-13 inducing peptides. More information on IL13Pred is available from its web-server https://webs.iiitd.edu.in/raghava/il13pred/stand.html. This page provides information about stnadalone version of IL13Pred. Please read/cite the content about the IL13Pred for complete information including algorithm behind IL13Pred.

Models: In this program, one model has been incorporated for predicting interleukin-13 inducing peptides. The model is trained on IL-13 inducing and non-inducing peptides.

Modules/Jobs: This program implements three modules (job types); i) Predict: for predictin of interleukin-13 inducing peptides, ii) Design: for generating all possible mutant peptides and computing interleukin-13 inducing potential (score) of peptides, iii) Scan: for creating all possible overlapping peptides of given length (window) and computing interleukin-13 inducing potential (score) of these overlapping peptides.

Minimum USAGE: Minimum usage is "il13pred -i peptide.fa," where peptide.fa is a input fasta file. This will predict the interleukin-13 inducing potential of sequence in fasta format. It will use other parameters by default. It will save output in "outfile.csv" in CSV (comma seperated variables).

Full Usage: Following is complete list of all options, you may get these options by "python il13pred.py -h"

usage: il13pred [-h] -i INPUT 
                        [-o OUTPUT]
			[-j {1,2,3}]
			[-t THRESHOLD] 
			[-w {8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35}] 
			[-d {1,2}]

Please provide following arguments

optional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Input: protein or peptide sequence in FASTA format or single sequence per line in single letter code
  -o OUTPUT, --output OUTPUT
                        Output: File for saving results by default outfile.csv
  -j {1,2,3}, --job {1,2,3}
                        Job Type: 1:predict, 2:design and 3:scan, by default 1
  -t THRESHOLD, --threshold THRESHOLD
                        Threshold: Value between 0 to 1 by default 0.06
  -w {8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35}, --winleng {8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35}
                        Window Length: 8 to 35 (scan mode only), by default 9
  -d {1,2}, --display {1,2}
                        Display: 1:Interleukin-13 inducing peptide, 2: All peptides, by default 1

Input File: It allow users to provide input in two format; i) FASTA format (standard) and ii) Simple Format. In case of simple format, file should have one peptide sequence in a single line in single letter code (eg. peptide.seq). Note: 1: In case of predict and design module (job), the length of peptide should be upto 35 amino acids. If a sequence with length more than 35 will be provided, program willtake first 35 residues, and ignore the rest. In case of scan module, minimum length of protein/peptide sequence should be more than or equal to window length (pattern), see peptide.fa. 2: Program will ignore peptides having length less than 8 residues (e.g., protein.fa).

Output File: Program will save the results in the CSV format, in case user do not provide output file name, it will be stored in "outfile.csv".

Threshold: User should provide threshold between 0 and 1, please note that the score is propotional to interleukin-13 inducing potential of peptide.

IL13Pred Package Files

It contantain following files, brief descript of these files given below

INSTALLATION : Installations instructions

LICENSE : License information

README.md : This file provide information about this package

XGB_model : Model file comprising the parameters of XGB classifier

il13pred.py : Main python program

peptide.fa : Example file contain peptide sequenaces in FASTA format

peptide.seq : Example file contain peptide sequenaces in simple format

protein.fa : Example file contain protein sequenaces in FASTA format

example_predict_output.csv : Example output file for predict module

example_scan_output.csv : Example output file for scan module

example_design_output.csv : Example output file for design module

Data : This folder contains the files required to run the in-built python scripts.